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← How do prediction markets work? Part 2 of 5

Order books vs AMMs in prediction markets

Prediction markets use one of two fundamentally different mechanisms to match buyers and sellers: a traditional orderbook, or an automated market maker (AMM). The choice shapes spreads, liquidity, and what kinds of markets can exist at all.

Order books vs AMMs in prediction markets


Orderbooks: match-when-they-meet

Kalshi and Polymarket both use orderbook models. Buyers post limit orders ("I'll buy YES at $0.55 or below"), sellers post limit orders ("I'll sell YES at $0.57 or above"), and trades execute when a buy price meets or exceeds a sell price. In liquid markets this produces tight spreads β€” often one or two cents β€” and excellent price discovery. In illiquid markets the orderbook can be empty on one side, and you simply cannot trade at any price.

AMMs: algorithmic quotes

Automated market makers replace the orderbook with a smart-contract liquidity pool that prices shares using a mathematical formula. The most famous is Robin Hanson's LMSR (Logarithmic Market Scoring Rule), which always provides a quote, even in dead markets, and bounds the market maker's maximum loss. The trade-off: AMMs give worse prices on large trades because the curve moves against you with size.

Which is better?

For high-volume markets β€” elections, major sports, macro data β€” orderbooks win on spread and execution quality. For long-tail questions with few traders, AMMs are the only way a market can exist at all. Many modern platforms use hybrid approaches: an orderbook for the main flow with an AMM filling in when the book is thin.